Practical Guide To Machine Vision Software
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Practical Guide To Machine Vision Software
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Author : Kye-Si Kwon
language : en
Publisher:
Release Date : 2014
Practical Guide To Machine Vision Software written by Kye-Si Kwon and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with COMPUTERS categories.
Practical Guide To Machine Vision Software
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Author : Kye-Si Kwon
language : en
Publisher: John Wiley & Sons
Release Date : 2015-04-20
Practical Guide To Machine Vision Software written by Kye-Si Kwon and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-04-20 with Computers categories.
For both students and engineers in R&D, this book explains machine vision in a concise, hands-on way, using the Vision Development Module of the LabView software by National Instruments. Following a short introduction to the basics of machine vision and the technical procedures of image acquisition, the book goes on to guide readers in the use of the various software functions of LabView's machine vision module. It covers typical machine vision tasks, including particle analysis, edge detection, pattern and shape matching, dimension measurements as well as optical character recognition, enabling readers to quickly and efficiently use these functions for their own machine vision applications. A discussion of the concepts involved in programming the Vision Development Module rounds off the book, while example problems and exercises are included for training purposes as well as to further explain the concept of machine vision. With its step-by-step guide and clear structure, this is an essential reference for beginners and experienced researchers alike.
A Guide For Machine Vision In Quality Control
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Author : Sheila Anand
language : en
Publisher: CRC Press
Release Date : 2019-12-10
A Guide For Machine Vision In Quality Control written by Sheila Anand and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-10 with Computer vision categories.
Machine Vision systems combine image processing with industrial automation. One of the primary areas of application of Machine Vision in the Industry is in the area of Quality Control. Machine vision provides fast, economic and reliable inspection that improves quality as well as business productivity. Building machine vision applications is a challenging task as each application is unique, with its own requirements and desired outcome. A Guide to Machine Vision in Quality Control follows a practitioner's approach to learning machine vision. The book provides guidance on how to build machine vision systems for quality inspections. Practical applications from the Industry have been discussed to provide a good understanding of usage of machine vision for quality control. Real-world case studies have been used to explain the process of building machine vision solutions. The book offers comprehensive coverage of the essential topics, that includes: Introduction to Machine Vision Fundamentals of Digital Images Discussion of various machine vision system components Digital image processing related to quality control Overview of automation The book can be used by students and academics, as well as by industry professionals, to understand the fundamentals of machine vision. Updates to the on-going technological innovations have been provided with a discussion on emerging trends in machine vision and smart factories of the future. Sheila Anand, a Doctorate in Computer Science, is working as Professor in the Department of Informaton Technology at Rajalakshmi Engineering College, Chennai, India. She has over three decades of experience in teaching, consultancy, and research. She has worked in the software industry and has extensive experience in development of software applications and in systems audit of financial, manufacturing, and trading organizations. She guides PhD aspirants and many of her research scholars have since been awarded their doctoral degree. She has published many papers in national and international journals and is a reviewer for several journals of repute. L. Priya is a PhD graduate working as Professor and Head, Department of Information Technology at Rajalakshmi Engineering College, Chennai, India. She has nearly two decades of teaching experience and good exposure to consultancy and research. She has delivered many invited talks, presented papers, and won several paper awards at international conferences. She has published several papers in international journals and is a reviewer for SCI indexed journals. Her areas of interest include machine vision, wireless communication, and machine learning.
Biologically Inspired Computer Vision
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Author : Gabriel Cristobal
language : en
Publisher: John Wiley & Sons
Release Date : 2015-11-16
Biologically Inspired Computer Vision written by Gabriel Cristobal and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-16 with Technology & Engineering categories.
As the state-of-the-art imaging technologies became more and more advanced, yielding scientific data at unprecedented detail and volume, the need to process and interpret all the data has made image processing and computer vision increasingly important. Sources of data that have to be routinely dealt with today's applications include video transmission, wireless communication, automatic fingerprint processing, massive databanks, non-weary and accurate automatic airport screening, robust night vision, just to name a few. Multidisciplinary inputs from other disciplines such as physics, computational neuroscience, cognitive science, mathematics, and biology will have a fundamental impact in the progress of imaging and vision sciences. One of the advantages of the study of biological organisms is to devise very different type of computational paradigms by implementing a neural network with a high degree of local connectivity. This is a comprehensive and rigorous reference in the area of biologically motivated vision sensors. The study of biologically visual systems can be considered as a two way avenue. On the one hand, biological organisms can provide a source of inspiration for new computational efficient and robust vision models and on the other hand machine vision approaches can provide new insights for understanding biological visual systems. Along the different chapters, this book covers a wide range of topics from fundamental to more specialized topics, including visual analysis based on a computational level, hardware implementation, and the design of new more advanced vision sensors. The last two sections of the book provide an overview of a few representative applications and current state of the art of the research in this area. This makes it a valuable book for graduate, Master, PhD students and also researchers in the field.
Practical Computer Vision
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Author : Abhinav Dadhich
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-02-05
Practical Computer Vision written by Abhinav Dadhich and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-02-05 with Computers categories.
A practical guide designed to get you from basics to current state of art in computer vision systems. Key Features Master the different tasks associated with Computer Vision and develop your own Computer Vision applications with ease Leverage the power of Python, Tensorflow, Keras, and OpenCV to perform image processing, object detection, feature detection and more With real-world datasets and fully functional code, this book is your one-stop guide to understanding Computer Vision Book Description In this book, you will find several recently proposed methods in various domains of computer vision. You will start by setting up the proper Python environment to work on practical applications. This includes setting up libraries such as OpenCV, TensorFlow, and Keras using Anaconda. Using these libraries, you'll start to understand the concepts of image transformation and filtering. You will find a detailed explanation of feature detectors such as FAST and ORB; you'll use them to find similar-looking objects. With an introduction to convolutional neural nets, you will learn how to build a deep neural net using Keras and how to use it to classify the Fashion-MNIST dataset. With regard to object detection, you will learn the implementation of a simple face detector as well as the workings of complex deep-learning-based object detectors such as Faster R-CNN and SSD using TensorFlow. You'll get started with semantic segmentation using FCN models and track objects with Deep SORT. Not only this, you will also use Visual SLAM techniques such as ORB-SLAM on a standard dataset. By the end of this book, you will have a firm understanding of the different computer vision techniques and how to apply them in your applications. What you will learn Learn the basics of image manipulation with OpenCV Implement and visualize image filters such as smoothing, dilation, histogram equalization, and more Set up various libraries and platforms, such as OpenCV, Keras, and Tensorflow, in order to start using computer vision, along with appropriate datasets for each chapter, such as MSCOCO, MOT, and Fashion-MNIST Understand image transformation and downsampling with practical implementations. Explore neural networks for computer vision and convolutional neural networks using Keras Understand working on deep-learning-based object detection such as Faster-R-CNN, SSD, and more Explore deep-learning-based object tracking in action Understand Visual SLAM techniques such as ORB-SLAM Who this book is for This book is for machine learning practitioners and deep learning enthusiasts who want to understand and implement various tasks associated with Computer Vision and image processing in the most practical manner possible. Some programming experience would be beneficial while knowing Python would be an added bonus.
Artificial Intelligence And Machine Learning
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Author : Khalid S. Soliman
language : en
Publisher: Springer Nature
Release Date : 2025-01-30
Artificial Intelligence And Machine Learning written by Khalid S. Soliman and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-30 with Computers categories.
The two-volume proceedings set CCIS 2299 and 2300, constitutes the refereed proceedings of the 43rd IBIMA Conference on Artificial intelligence and Machine Learning, IBIMA-AI 2024, held in Madrid, Spain, in June 26–27, 2024. The 44 full papers and 18 short papers included in this book were carefully reviewed and selected from 119 submissions. They were organized in topical sections as follows: Part I: Artificial Intelligence and Machine Learning; Information Systems and Communications Technologies. Part II: Artificial Intelligence and Machine Learning ; Software Engineering; Computer Security and Privacy.
Practical Guide To Simulation In Delivery Room Emergencies
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Author : Gilda Cinnella
language : en
Publisher: Springer Nature
Release Date : 2023-06-13
Practical Guide To Simulation In Delivery Room Emergencies written by Gilda Cinnella and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-13 with Medical categories.
In this book the use of hybrid simulation in delivery room emergencies is described and shown. The use of a patient actor combined with a task trainer within the same session substantially improve the training for practical management of intrapartum emergencies in real life, reducing the risk of failure of operative vaginal delivery and of related adverse events, including perinatal or maternal complications. Furthermore, simulation with high reality computerized mannequin and scenography of emergency situation can improve technical and manual skills of the participants. For this book and the related videos, a new generation of mannequins suitable for both clinical manoeuvres and ultrasound examination is used to simulate all clinical scenarios of emergency that can happen in the delivery room for both the mother and the child. This unique book is a useful tool for medical students, residents, practicing pediatricians, anesthetists, obstetricians and all health care professionals working in the delivery room in their ability to deal with critical and emergency situations with safety and good medical practice.
Advanced Technologies Systems And Applications Vii
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Author : Naida Ademović
language : en
Publisher: Springer Nature
Release Date : 2022-10-15
Advanced Technologies Systems And Applications Vii written by Naida Ademović and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-15 with Technology & Engineering categories.
This book presents a collection of articles on the advanced and interdisciplinary application of innovative technologies. Scientific investigations and results of the conference 13th Days of Bosnian-Herzegovinian American Academy of Art and Sciences held in Sarajevo, Bosnia and Herzegovina, June 23-26, 2022, are presented in this book. The up-to-date advances in various fields of engineering have been presented through numerous papers spanning the disciplines of civil engineering, mechanical engineering, advanced electrical power systems, computer modeling and simulations for engineering applications, computer science and artificial intelligence, geodesy and geoinformation, data science and geographic information systems and information and communication technologies. The editors would like to extend special gratitude to all the chairs of the planned symposia of the 13th Days of BHAAAS for their dedicated work in the production of this book.
Deep Learning For Coders With Fastai And Pytorch
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Author : Jeremy Howard
language : en
Publisher: O'Reilly Media
Release Date : 2020-06-29
Deep Learning For Coders With Fastai And Pytorch written by Jeremy Howard and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-29 with Computers categories.
Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala
Interpretable Machine Learning
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Author : Christoph Molnar
language : en
Publisher: Lulu.com
Release Date : 2020
Interpretable Machine Learning written by Christoph Molnar and has been published by Lulu.com this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Computers categories.
This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.